Data Engineer

Job Title: Data Engineer

Location: Jersey City, NJ (Hybrid)

Duration: 6 Months Contract

Experience: 5+ years

Interview process:

L1 Video interview with Imp panel

L2 2-3 round of in-person interview with client in 1 day

Position Summary

We are seeking a skilled Data Engineer to design, develop, and support modern data platforms and pipelines that power analytics, reporting, and AI-driven solutions. The ideal candidate will have strong expertise in Snowflake, Python, SQL, AWS, Oracle, and Apache Airflow, with exposure to AI/Generative AI technologies.

Responsibilities

• Design, build, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop and optimize data solutions in Snowflake, including data modeling, performance tuning, and automation.
• Integrate and transform data from Oracle, APIs, AWS services, and other enterprise systems.
• Build and manage workflow orchestration using Apache Airflow.
• Develop cloud-native data solutions utilizing AWS services such as S3, Glue, Lambda, and ECS/EKS.
• Ensure data quality, reliability, security, and governance across the data platform.
• Support AI and analytics initiatives by preparing datasets and building pipelines for ML and Generative AI use cases.
• Collaborate closely with architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• 5+ years of experience in Data Engineering or Data Platform development.
• Strong hands-on expertise in:
• Snowflake
• SQL (Advanced)
• Python (Advanced)
• AWS
• Oracle
• Apache Airflow
• Experience designing and supporting enterprise-scale data pipelines and data warehouses.
• Strong understanding of data modeling, performance optimization, and cloud-based data architectures.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Snowpark, Streams, Tasks, and Dynamic Tables.
• Exposure to AI/ML, Generative AI, RAG architectures, or vector databases.
• Experience with Spark, Kafka, or Databricks.
• SnowPro and/or AWS certifications.
• Experience in financial services or capital markets environments.

Key Skills

Snowflake | SQL | Python | AWS | Oracle | Airflow | ETL/ELT | Data Warehousing | Data Modeling | Snowpark | AI/GenAI | Data Governance

Ideal Candidate:

A hands-on engineer with deep SQL and Python expertise, capable of building scalable cloud-native data solutions while helping enable the organization's AI and analytics strategy.